Create The AI Output Semantic Regression Tester, a testing workbench that detects meaningful behavior changes between two versions of an AI application's output.
Allow users to import baseline outputs, candidate outputs, input prompts, expected requirements, and optional structured schemas.
The application should:
Compare exact text changes separately from semantic or requirement-level differences.
Detect missing requirements, changed quantities, contradictory statements, and altered commitments.
Validate structured outputs against user-defined schemas.
Identify changes in tone, format, length, and required terminology.
Let users define critical requirements that must never regress.
Group failures by severity and affected test case.
Display side-by-side output comparisons with highlighted differences.
Generate regression reports and reusable test fixtures.
Support human review for subjective comparisons.
Include examples for customer-support responses, document extraction, and code explanations. Use deterministic checks for measurable requirements and clearly label any heuristic semantic assessment. Do not treat text similarity as proof of behavioral equivalence. Build a functional interface that works with manually supplied outputs and requires no external model API.
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